v0.49.1
Browse filesSee https://github.com/qualcomm/ai-hub-models/releases/v0.49.1 for changelog.
README.md
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ResNeXt101 is a machine learning model that can classify images from the Imagenet dataset. It can also be used as a backbone in building more complex models for specific use cases.
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This is based on the implementation of ResNeXt101 found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py).
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This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/
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Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device.
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| Runtime | Precision | Chipset | SDK Versions | Download |
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|---|---|---|---|---|
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| ONNX | float | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.
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| ONNX | w8a8 | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.
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| QNN_DLC | float | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.
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| QNN_DLC | w8a8 | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.
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| TFLITE | float | Universal | QAIRT 2.43, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.
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| TFLITE | w8a8 | Universal | QAIRT 2.43, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.
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For more device-specific assets and performance metrics, visit **[ResNeXt101 on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/resnext101)**.
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### Option 2: Export with Custom Configurations
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Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/
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- Custom weights (e.g., fine-tuned checkpoints)
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- Custom input shapes
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- Target device and runtime configurations
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This option is ideal if you need to customize the model beyond the default configuration provided here.
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See our repository for [ResNeXt101 on GitHub](https://github.com/qualcomm/ai-hub-models/
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## Model Details
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## Performance Summary
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| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
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|---|---|---|---|---|---|---
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| ResNeXt101 | ONNX | float | Snapdragon®
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| ResNeXt101 | ONNX | float | Snapdragon®
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| ResNeXt101 | ONNX | float | Snapdragon®
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| ResNeXt101 | ONNX | float |
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| ResNeXt101 | ONNX | float | Qualcomm®
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| ResNeXt101 | ONNX | float |
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| ResNeXt101 | ONNX | float | Snapdragon® 8 Elite
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| ResNeXt101 | ONNX | w8a8 | Snapdragon®
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| ResNeXt101 | ONNX | w8a8 | Snapdragon®
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| ResNeXt101 | ONNX | w8a8 | Snapdragon®
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| ResNeXt101 | ONNX | w8a8 |
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| ResNeXt101 | ONNX | w8a8 | Qualcomm®
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| ResNeXt101 | ONNX | w8a8 | Qualcomm®
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| ResNeXt101 | ONNX | w8a8 | Qualcomm®
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| ResNeXt101 | ONNX | w8a8 |
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| ResNeXt101 | ONNX | w8a8 | Snapdragon®
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| ResNeXt101 | ONNX | w8a8 | Snapdragon®
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| ResNeXt101 | QNN_DLC | float | Snapdragon®
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| ResNeXt101 | QNN_DLC | float | Snapdragon®
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| ResNeXt101 | QNN_DLC | float | Snapdragon®
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| ResNeXt101 | QNN_DLC | float |
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| ResNeXt101 | QNN_DLC | float | Qualcomm®
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| ResNeXt101 | QNN_DLC | float | Qualcomm®
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| ResNeXt101 | QNN_DLC | float | Qualcomm®
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| ResNeXt101 | QNN_DLC | float | Qualcomm®
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| ResNeXt101 | QNN_DLC | float | Qualcomm®
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| ResNeXt101 | QNN_DLC | float | Qualcomm®
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| ResNeXt101 | QNN_DLC | float |
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| ResNeXt101 | QNN_DLC | float | Snapdragon® 8 Elite
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| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon®
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| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon®
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| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon®
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| ResNeXt101 | QNN_DLC | w8a8 |
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| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm®
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| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm®
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| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm®
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| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm®
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| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm®
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| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm®
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| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm®
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| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm®
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| ResNeXt101 | QNN_DLC | w8a8 |
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| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon®
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| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon®
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| ResNeXt101 | TFLITE | float | Snapdragon® 8 Gen
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| ResNeXt101 | TFLITE | float |
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| ResNeXt101 | TFLITE | float | Qualcomm®
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| ResNeXt101 | TFLITE | float | Qualcomm®
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| ResNeXt101 | TFLITE | float | Qualcomm® QCS9075 | 10.041 ms | 0 - 174 MB | NPU
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| ResNeXt101 | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 9.
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| ResNeXt101 | TFLITE | float | Qualcomm® SA7255P | 35.
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| ResNeXt101 | TFLITE | float | Qualcomm® SA8295P | 10.
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| ResNeXt101 | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 3.
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| ResNeXt101 | TFLITE |
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| ResNeXt101 | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile |
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| ResNeXt101 | TFLITE | w8a8 | Qualcomm® QCS6490 | 8.
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| ResNeXt101 | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 6.
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| ResNeXt101 | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 2.
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| ResNeXt101 | TFLITE | w8a8 | Qualcomm® SA8775P |
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| ResNeXt101 | TFLITE | w8a8 | Qualcomm® QCS9075 | 2.
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| ResNeXt101 | TFLITE | w8a8 | Qualcomm® QCM6690 |
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| ResNeXt101 | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 3.
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| ResNeXt101 | TFLITE | w8a8 | Qualcomm® SA7255P | 6.
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| ResNeXt101 | TFLITE | w8a8 | Qualcomm® SA8295P | 4.
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| ResNeXt101 | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 1.
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| ResNeXt101 | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 3.
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| ResNeXt101 | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 1.473 ms | 0 - 210 MB | NPU
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## License
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* The license for the original implementation of ResNeXt101 can be found
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ResNeXt101 is a machine learning model that can classify images from the Imagenet dataset. It can also be used as a backbone in building more complex models for specific use cases.
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This is based on the implementation of ResNeXt101 found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py).
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This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/tree/v0.49.1/qai_hub_models/models/resnext101) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
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Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device.
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| Runtime | Precision | Chipset | SDK Versions | Download |
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|---|---|---|---|---|
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| ONNX | float | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.49.1/resnext101-onnx-float.zip)
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| ONNX | w8a8 | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.49.1/resnext101-onnx-w8a8.zip)
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| QNN_DLC | float | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.49.1/resnext101-qnn_dlc-float.zip)
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| QNN_DLC | w8a8 | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.49.1/resnext101-qnn_dlc-w8a8.zip)
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| TFLITE | float | Universal | QAIRT 2.43, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.49.1/resnext101-tflite-float.zip)
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| TFLITE | w8a8 | Universal | QAIRT 2.43, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.49.1/resnext101-tflite-w8a8.zip)
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For more device-specific assets and performance metrics, visit **[ResNeXt101 on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/resnext101)**.
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### Option 2: Export with Custom Configurations
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Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/tree/v0.49.1/qai_hub_models/models/resnext101) Python library to compile and export the model with your own:
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- Custom weights (e.g., fine-tuned checkpoints)
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- Custom input shapes
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- Target device and runtime configurations
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This option is ideal if you need to customize the model beyond the default configuration provided here.
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See our repository for [ResNeXt101 on GitHub](https://github.com/qualcomm/ai-hub-models/tree/v0.49.1/qai_hub_models/models/resnext101) for usage instructions.
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## Model Details
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## Performance Summary
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| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
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|---|---|---|---|---|---|---
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| ResNeXt101 | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.05 ms | 1 - 203 MB | NPU
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| ResNeXt101 | ONNX | float | Snapdragon® X2 Elite | 3.101 ms | 173 - 173 MB | NPU
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| ResNeXt101 | ONNX | float | Snapdragon® X Elite | 6.692 ms | 172 - 172 MB | NPU
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| ResNeXt101 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 4.503 ms | 0 - 373 MB | NPU
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| ResNeXt101 | ONNX | float | Qualcomm® QCS8550 (Proxy) | 6.643 ms | 0 - 199 MB | NPU
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| ResNeXt101 | ONNX | float | Qualcomm® QCS9075 | 9.779 ms | 0 - 4 MB | NPU
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| ResNeXt101 | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 3.88 ms | 0 - 175 MB | NPU
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| ResNeXt101 | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 1.576 ms | 0 - 215 MB | NPU
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| ResNeXt101 | ONNX | w8a8 | Snapdragon® X2 Elite | 1.386 ms | 87 - 87 MB | NPU
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| ResNeXt101 | ONNX | w8a8 | Snapdragon® X Elite | 3.139 ms | 87 - 87 MB | NPU
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| ResNeXt101 | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 2.154 ms | 0 - 259 MB | NPU
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| ResNeXt101 | ONNX | w8a8 | Qualcomm® QCS6490 | 112.681 ms | 3 - 36 MB | CPU
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| ResNeXt101 | ONNX | w8a8 | Qualcomm® QCS8550 (Proxy) | 2.937 ms | 0 - 100 MB | NPU
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| ResNeXt101 | ONNX | w8a8 | Qualcomm® QCS9075 | 3.135 ms | 0 - 3 MB | NPU
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| ResNeXt101 | ONNX | w8a8 | Qualcomm® QCM6690 | 73.093 ms | 0 - 12 MB | CPU
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| ResNeXt101 | ONNX | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 1.859 ms | 0 - 224 MB | NPU
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| ResNeXt101 | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 68.135 ms | 0 - 12 MB | CPU
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| ResNeXt101 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.093 ms | 1 - 195 MB | NPU
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| ResNeXt101 | QNN_DLC | float | Snapdragon® X2 Elite | 3.768 ms | 1 - 1 MB | NPU
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| ResNeXt101 | QNN_DLC | float | Snapdragon® X Elite | 6.939 ms | 1 - 1 MB | NPU
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| ResNeXt101 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 4.642 ms | 0 - 371 MB | NPU
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| ResNeXt101 | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 35.894 ms | 1 - 191 MB | NPU
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| ResNeXt101 | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 6.836 ms | 1 - 3 MB | NPU
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| ResNeXt101 | QNN_DLC | float | Qualcomm® SA8775P | 10.31 ms | 1 - 203 MB | NPU
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| ResNeXt101 | QNN_DLC | float | Qualcomm® QCS9075 | 9.988 ms | 1 - 3 MB | NPU
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| ResNeXt101 | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 9.882 ms | 0 - 313 MB | NPU
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| ResNeXt101 | QNN_DLC | float | Qualcomm® SA7255P | 35.894 ms | 1 - 191 MB | NPU
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| ResNeXt101 | QNN_DLC | float | Qualcomm® SA8295P | 10.937 ms | 1 - 140 MB | NPU
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| ResNeXt101 | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 3.993 ms | 1 - 189 MB | NPU
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| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 1.525 ms | 0 - 210 MB | NPU
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| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 1.765 ms | 0 - 0 MB | NPU
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| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon® X Elite | 3.078 ms | 0 - 0 MB | NPU
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| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 2.138 ms | 0 - 250 MB | NPU
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| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® QCS6490 | 9.267 ms | 0 - 2 MB | NPU
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| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® QCS8275 (Proxy) | 6.517 ms | 0 - 206 MB | NPU
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| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® QCS8550 (Proxy) | 2.847 ms | 0 - 4 MB | NPU
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| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® SA8775P | 3.507 ms | 0 - 207 MB | NPU
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| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® QCS9075 | 3.137 ms | 0 - 2 MB | NPU
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| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® QCM6690 | 33.668 ms | 0 - 370 MB | NPU
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| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® QCS8450 (Proxy) | 3.902 ms | 0 - 250 MB | NPU
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| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® SA7255P | 6.517 ms | 0 - 206 MB | NPU
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| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® SA8295P | 4.257 ms | 0 - 209 MB | NPU
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| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 1.809 ms | 0 - 207 MB | NPU
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| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 4.065 ms | 0 - 241 MB | NPU
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| ResNeXt101 | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.093 ms | 0 - 401 MB | NPU
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| ResNeXt101 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 4.642 ms | 0 - 580 MB | NPU
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| ResNeXt101 | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 35.913 ms | 0 - 396 MB | NPU
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| ResNeXt101 | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 6.793 ms | 0 - 2 MB | NPU
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| ResNeXt101 | TFLITE | float | Qualcomm® SA8775P | 45.167 ms | 0 - 396 MB | NPU
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| ResNeXt101 | TFLITE | float | Qualcomm® QCS9075 | 10.041 ms | 0 - 174 MB | NPU
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| ResNeXt101 | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 9.882 ms | 0 - 511 MB | NPU
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| ResNeXt101 | TFLITE | float | Qualcomm® SA7255P | 35.913 ms | 0 - 396 MB | NPU
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| ResNeXt101 | TFLITE | float | Qualcomm® SA8295P | 10.968 ms | 0 - 336 MB | NPU
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| ResNeXt101 | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 3.96 ms | 0 - 398 MB | NPU
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| ResNeXt101 | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 1.472 ms | 0 - 211 MB | NPU
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| ResNeXt101 | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 2.001 ms | 0 - 257 MB | NPU
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| ResNeXt101 | TFLITE | w8a8 | Qualcomm® QCS6490 | 8.87 ms | 0 - 88 MB | NPU
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| ResNeXt101 | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 6.29 ms | 0 - 210 MB | NPU
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| ResNeXt101 | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 2.664 ms | 0 - 4 MB | NPU
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| ResNeXt101 | TFLITE | w8a8 | Qualcomm® SA8775P | 3.349 ms | 0 - 211 MB | NPU
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| ResNeXt101 | TFLITE | w8a8 | Qualcomm® QCS9075 | 2.959 ms | 0 - 89 MB | NPU
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| ResNeXt101 | TFLITE | w8a8 | Qualcomm® QCM6690 | 28.419 ms | 0 - 370 MB | NPU
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+
| ResNeXt101 | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 3.719 ms | 0 - 249 MB | NPU
|
| 130 |
+
| ResNeXt101 | TFLITE | w8a8 | Qualcomm® SA7255P | 6.29 ms | 0 - 210 MB | NPU
|
| 131 |
+
| ResNeXt101 | TFLITE | w8a8 | Qualcomm® SA8295P | 4.076 ms | 0 - 213 MB | NPU
|
| 132 |
+
| ResNeXt101 | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 1.773 ms | 0 - 209 MB | NPU
|
| 133 |
+
| ResNeXt101 | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 3.96 ms | 0 - 241 MB | NPU
|
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|
|
| 134 |
|
| 135 |
## License
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| 136 |
* The license for the original implementation of ResNeXt101 can be found
|